TY - JOUR T1 - A binary segmentation approach for boxing ribosome particles in cryo EM micrographs. JF - J Struct Biol Y1 - 2004 A1 - Adiga, Umesh A1 - Malladi, Ravi A1 - Baxter, Bill A1 - Glaeser, Robert M KW - Algorithms KW - Anisotropy KW - Automatic Data Processing KW - Cryoelectron Microscopy KW - Image Enhancement KW - Image Processing, Computer-Assisted KW - Particle Size KW - Pattern Recognition, Automated KW - Ribosomes KW - Software Design AB -

Three-dimensional reconstruction of ribosome particles from electron micrographs requires selection of many single-particle images. Roughly 100,000 particles are required to achieve approximately 10 A resolution. Manual selection of particles, by visual observation of the micrographs on a computer screen, is recognized as a bottleneck in automated single-particle reconstruction. This paper describes an efficient approach for automated boxing of ribosome particles in micrographs. Use of a fast, anisotropic non-linear reaction-diffusion method to pre-process micrographs and rank-leveling to enhance the contrast between particles and the background, followed by binary and morphological segmentation constitute the core of this technique. Modifying the shape of the particles to facilitate segmentation of individual particles within clusters and boxing the isolated particles is successfully attempted. Tests on a limited number of micrographs have shown that over 80% success is achieved in automatic particle picking.

VL - 145 UR - http://www.ncbi.nlm.nih.gov/pubmed/15065681 IS - 1-2 ER -